Presentation and rendering of images, graphics and video on data processing systems and user terminals, such as computers, and in particular on mobile terminals have increased tremendously the last years. This increase in image rendering and utilization of vastly different data processing and presenting systems and terminals often requires resizing images between different image formats adapted for different presenting systems and terminals.
When images, e.g. images in a video sequence, are resized and the new image dimension has a new width and height ratio, borders are typically positioned above and below and/or to the left and right of the resized image. Such a resizing is employed e.g. in widescreen format adaptation. This border positioning is particularly common in scenarios where the resizing is time-critical and the computional complexity needs to be low, such as when transcoding real-time media and/or when the transcoding/resizing is performed by mobile terminals and other thin clients.
FIG. 1 illustrates such a prior technique employed in resizing images. In this figure an original, possibly resized, image or image frame 10 is positioned within a new image frame 30 having a different width and height ratio compared to the original image frame 10. According to the prior art techniques, the (resized) original image frame 10 is placed as symmetrical as possible within the new image frame 30 so that the actual visible image 10 is placed in the middle of the new frame 30. Note further the borders that are found to the left and right of the original image frame 10.
Rendering of images is a computationally expensive task in terms of memory bandwidth and processing power required for the graphic systems. For example, images are costly both in terms of memory, the images must be placed on fast on-chip memory, and in terms of memory bandwidth, an image can be accessed several times to draw a single pixel.
In order to reduce the bandwidth and processing power requirements, an image compressing or encoding method or system is typically employed. Such an encoding system should result in more efficient usage of expensive on-chip memory and lower memory bandwidth during rendering and, thus, in lower power consumption and/or faster rendering.
When compressing an image, sharp edges generally require more bits than smooth edges to be represented with a similar quality. Another characteristic of image compressions is the artifact known as bleeding. This bleeding phenomenon implies that colors tend to smear. Bleeding becomes more prominent when a colorful region is located adjacent to a region with less color, or only one color.